We are looking for two Data Analysts: one specializing in data engineering & migration and another focused on data pipeline & automation. Applicants must have strong communication skills in English, both spoken and written, and all resumes should be submitted in English.

Key Responsibilities - Improve data pipelines with automation and quality checks to ensure accuracy, consistency, and reliability, reducing manual intervention and minimizing errors.

- Lead migration of legacy systems to new platforms, performing thorough analysis, seamless data transfer, integration, and performance enhancement while maintaining continuity.

Requirements Required Education - Bachelor’s degree in Computer Science, Engineering, Information Systems, or a related field (preferred).

- Equivalent hands‑on experience is highly valued.

Required Experience - 4 to 7 years as a Data Engineer.

- Practical, hands‑on expertise beyond theoretical knowledge.

Required

Background / Industry Experience (Both roles) - Experience with cloud‑based data platforms and environments.

- Strong SQL skills and data modeling for data warehouses.
- Strong Python skills (notably in notebooks) for building and maintaining data workflows.
- Experience developing and maintaining ETL/ELT processes.
- Familiarity with data warehouses used by reporting/business teams.
- Version control expertise using Git/GitHub in collaborative settings.
- Understanding of data engineering best practices, including pipeline orchestration, dependency management, data quality, validation, and monitoring fundamentals. Required for Migration‑focused Role - Hands‑on data migration experience.
- Schema mapping and transformation.
- Data reconciliation and validation (strong focus).
- Data quality checks, integrity validation, and issue resolution.
- Backfills and historical data handling.




- Cutover planning and execution. Required for Automation‑focused Role - Experience building and maintaining automated data pipelines.
- Scheduling, orchestration, and failure handling.
- Workflow reliability, monitoring, and repeatability. Preferred - Experience within Microsoft Fabric or the broader Microsoft Azure data ecosystem.
- Experience with orchestration tools such as Apache Airflow, Azure Data Factory, or Fabric pipelines.
- Experience with data quality and observability practices: validation frameworks, alerting, SLAs, monitoring.
- Experience optimizing performance in data environments: query tuning, partitioning, indexing, cost optimization.
- Familiarity with modern data formats and large‑scale processing: Parquet, Delta, incremental processing patterns.
- Experience integrating with external systems: REST APIs, authentication, retries, error handling.
- Exposure to CI/CD practices for data workflows: Git‑based deployments, PR workflows, environment promotion.

Key Soft

Skills - Clear communication: explain data issues, trade‑offs, and results to technical and business stakeholders.

- Ownership & accountability: take end‑to‑end responsibility for pipelines, data quality, and outcomes.
- Problem‑solving mindset: debug complex data issues and resolve ambiguity independently.
- Collaboration: work effectively across engineering, analytics, and business teams.
- Adaptability: thrive in evolving environments (migration, changing requirements, new tools).

Technical Skills

Proficiency in SQL, Python, cloud technologies, and data competency.

Benefits - USD base salary.

- Paid Time Off (PTO) after 6 months of service.
- Full‑time opportunity.
- Completely remote work environment.

Typical work schedule: 9:00 am to 6:00 pm Eastern Time, Monday through Friday, with occasional additional hours as needed.

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